Development of a Medical Test.
The probability of curing a disease (e.g. a cancer disease) is many times predominantly dependent from an early as possible detection of the disease. It is also often advantageous to detect a predisposition for a disease or if for example the disease is already advanced to make an estimation for the most promising treatment for the disease. Such an early as possible detection, prediction or estimation reduces the costs for direct and associated medical treatment. It ensures also a higher quality of life for the affected patient.
This leads to the situation that a lot of samples derived from individuals with a suspected disease have to be tested, the majority may not be affected by the disease. Or, in case of patients with a diagnosed disease, a lot of samples have to be tested, and only a small percentage will respond to a certain treatment.
In general, it is desirable that a test should have a high as possible sensitivity, a high as possible specificity and a high as possible accuracy. Sensitivity is a measure of a test's ability to correctly detect the target disease in an individual being tested. A test having poor sensitivity produces a high rate of false negatives, i.e., individuals who have the disease but are falsely identified as being free of that particular disease. The potential danger of a false negative is that the diseased individual will remain undiagnosed and untreated for some period of time, during which the disease may progress to a later stage wherein treatments, if any, may be less effective. Mathematical it can be described as: Sensitivity=TP/(TP+FN). Thereby TP represents a true positive result and FN a false negative result. A true positive result means that the test is positive and the condition is present while a false negative result is where the test is negative but the condition is not present.
An example of a test that has low sensitivity is a protein-based blood test for HIV. This type of test exhibits poor sensitivity because it fails to detect the presence of the virus until the disease is well established and the virus has invaded the bloodstream in substantial numbers. In contrast, an example of a test that has high sensitivity is viral-load detection using the polymerase chain reaction (PCR). High sensitivity is achieved because this type of test can detect very small quantities of the virus. High sensitivity is particularly important when the consequences of missing a diagnosis are high.
Specificity, on the other hand, is a measure of a test's ability to identify accurately patients who are free of the disease state. A test having poor specificity produces a high rate of false positives, i.e., individuals who are falsely identified as having the disease. A drawback of false positives is that they force patients to undergo unnecessary medical procedures or treatments with their attendant risks, emotional and financial stresses, and which could have adverse effects on the patient's health. A feature of diseases which makes it difficult to develop diagnostic tests with high specificity is that disease mechanisms, particularly in cancer, often involve a plurality of genes and proteins. Additionally, certain proteins may be elevated for reasons unrelated to a disease state. Mathematical specificity can be described as: Specificity=TN/(FP+TN). Thereby TN represents a true negative result and FP a false positive result. A true negative result is where the test is negative and the condition is not present. A false positive result is where the test is positive but the condition is not present.
An example of a test that has high specificity is a gene-based test that can detect a p53 mutation. Specificity is important when the cost or risk associated with further diagnostic procedures or further medical intervention are very high.
Accuracy is a measure of a test's ability on one hand to correctly detect the target disease in an individual being tested and simultaneously on the other to identify accurately patients who are free of the disease state. So accuracy describes a test's sensitivity and specificity simultaneously. Mathematical it is defined as: Accuracy=(TP+TN)/N, wherein TP represents true positive results, TN true negative results and N the number of patients tested.
In general, because of self-evident reasons, a test of choice would be further characterized by at least one of the following criteria, but of course preferably by all of them: (i) high degree of standardization, (ii) large capability for automatization, (iii) avoidance of cross-contaminations of samples, (iv) low handling effort, (v) low cost, (vi) ease of handling, (vii) high reproducibility, (viii) high reliability.
Of course, all of the above described specifications apply not only for the test itself. They also apply to the workflow from collecting a sample to the actual start of the test. In other words a suitable workflow should enable a test with said specifications.
Starting Material for a Test.
It is advantageous for a test with regard to cost reduction and to a high quality of life of the patient that it can be performed non-invasively. If this is not possible, it is desirably to perform it by invasive means which affect as less as possible the patient, which are easy to perform, which cause low costs or combinations thereof. Because of that, remote samples like for example blood, sputum, stool or body fluids are the starting material of choice for a test.
However, the use of remote samples is quite limited by the low amount of DNA, in particular by the low amount of DNA which originates by the diseased cell or tissue. Therefore the workflow from the sample collecting to the start of the test has to be characterized by high yields of DNA.
In most cases the DNA of interest is very diluted in the sample. Typically less than 1% is relevant for the test underlying question. This emphasis that a workflow for collecting, providing, and processing DNA prior the test has to be characterized by high yields of DNA.
A further difficulty, for the use of remote samples is that the samples can be contaminated by a large amount of cells and therewith DNA. The contamination is thereby completely unrelated to the question on which the test is based on. For example such contaminations are bacteria like E. Coli in stool samples or red blood cells in plasma or serum samples. These contaminations are especially critical if they are interfere with the detection of the DNA of interest or if they are present in large amounts. In last case, the percentage of the DNA of interest becomes so small that it can no more be detected. Because of that a workflow for collecting, providing and processing DNA prior a test has to be sure to efficiently remove such contaminations.
Furthermore, the DNA of interest might be partially degraded in a remote sample. This depends on the type of the remote sample and also on the way of collecting and handling the remote sample. A fragmentation of DNA in remote sample down to a fragment size of 100 bp and under it is possible. Therefore a workflow from collecting a sample to the start of a test should ensure that small DNA fragments as well as large DNA fragments are provided and that the DNA does not get further fragmented.
Numerous documents exist which address these problems. Exemplary only the following are cited herein: Diehl F., et al. (2005) PNAS 102(45), 16368-16373; and Li J., et al. (2006) Journal of Molecular Diagnostics, 8(1), 22-30.
Methylation Analysis.
As revealed in recent years, one of the most powerful and promising approaches for detecting a disease, the predisposition for a disease or for estimating a probable response with respect to a certain disease treatment is the methylation analysis of the patient's genomic DNA.
Many diseases, in particular cancer diseases, are accompanied by modified gene expression. This may be a mutation of the genes themselves, which leads to an expression of modified proteins or to an inhibition or over-expression of the proteins or enzymes. A modulation of the expression may however also occur by epigenetic modifications, in particular by changes in the DNA methylation pattern. Such epigenetic modifications do not affect the actual DNA coding sequence. It has been found that DNA methylation processes have substantial implications for health, and it seems to be clear that knowledge about methylation processes and modifications of the methyl metabolism and DNA methylation are essential for understanding diseases, for the prophylaxis, diagnosis and therapy of diseases.
The precise control of genes, which represent a small part only of the complete genome of mammals, involves regulation in consideration of the fact that the main part of the DNA in the genome is not coding. The presence of such ‘trunk’ DNA containing introns, repetitive elements and potentially actively transposable elements, requires effective mechanisms for their durable suppression (silencing). Apparently, the methylation of cytosine by S-adenosylmethionine (SAM) dependent DNA methyl transferases, which form 5-methylcytosine, represents such a mechanism for the modification of DNA-protein interactions. Genes can be transcribed by methylation-free promoters, even when adjacent transcribed or not-transcribed regions are widely methylated. This permits the use and regulation of promoters of functional genes, whereas the trunk DNA including the transposable elements is suppressed. Methylation also takes place for the long-term suppression of X-linked genes and may lead to either a reduction or an increase of the degree of transcription, depending on where the methylation in the transcription units occurs.
Nearly the complete natural DNA methylation in mammals is restricted to cytosine-guanosine (CpG) dinucleotide palindrome sequences, which are controlled by DNA methyl transferases. CpG dinucleotides are about 1 to 2% of all dinucleotides and are concentrated in CpG islands. According to an art-recognized definition, a region is considered as a CpG island when the C+G content over 200 bp is at least 50% and the percentage of the observed CG dinucleotides in comparison to the expected CG dinucleotides is larger than 0.6 (Gardiner-Garden, M., Frommer, M. (1987) J. Mol. Biol. 196, 261-282). Typically, CpG islands have at least 4 CpG dinucleotides in a sequence of a length of 100 bp.
CpG islands located in promotor regions frequently have a regulatory function for the expression of the corresponding gene. For example, in case the CpG island is hypomethylated, the gene can be expressed. On the other hand, hypermethylation frequently leads to a suppression of the expression. Normally tumour suppressor genes are hypomethylated. But if they become hypermethylated, their expression becomes suppressed. This is observed many times in tumour tissues. By contrast, oncogenes are hypermethylated in healthy tissue, whereas they are hypomethylated in many times in tumour tissues.
The methylation of cytosine has the effect that the binding of proteins is normally prohibited which regulate the transcription of genes. This leads to an alteration of the expression of the gene. Relating to cancer, the expression of genes regulating cell division are thereby alterated, for example, the expression of an apoptotic gene is down regulated, while the expression of an oncogene is up regulated. Additionally, hypermethylation may have a long term influence on regulation. Proteins, which deacetylate histones, are able to bind via their 5-methylcytosine binding domain to the DNA when the cytosines get methylated. This results in a deacetylation of the histones, which itself leads to a tighter package of the DNA. Because of that, regulatory proteins are not precluded from binding to the DNA.
The efficient detection of DNA methylation patterns consequently is an important tool for developing new approaches to understand diseases, for the prevention, diagnosis and treatment of diseases and for the screening for disease associated targets. But on the other hand, methods for an efficient detection of DNA methylation require high quality standards in regard to the starting material the genomic DNA. Preferably, the standards are:                I) A sufficient amount of DNA characterized by a methylation pattern specific for a defined condition is comprised in the employed DNA sample. This sufficient amount of DNA is dependent on the method for detecting the methylation pattern as well as on the methylation pattern itself. Typical values are in the range of about 20 pg to about 10 ng. But it has to be considered that the actual amount of this DNA in a sample taken from a patient has to be much higher, at least by a factor of 4-8 times. The reason for this is the loss of DNA during sample providing and sample processing for example DNA isolation;        II) The employed DNA sample has to be free of DNA which might interfere with a choosen method for detecting a desired methylation pattern;        III) The employed DNA sample should preferably also not contain large contamination of DNA which is unrelated to the underlying problem. This is for example E. Coli DNA in stool samples or DNA of red blood cells in plasma or serum samples; and        IV) The employed DNA should be preferably free of associated or linked proteins, peptides, amino acids, RNA as well as of nucleotides or bases, which are not part of the DNA backbone. These may sterically hinder the detection of methylation.        
Pronounced Need in the Art.
At the moment the applicant is not aware of any relevant prior art method. Thereby relevant means that it fulfills the criteria as specified above for providing DNA from remote samples, for providing DNA suitable for methylation analysis, and for medical tests in general.
As the closest prior art, the following documents may be considered: Utting M., et al. (2002) Clinical Cancer Research 8, 35-40. This study indicates that microsatellite marker analysis using free-floating DNA of urine or blood could be relevant for diagnosis and screening of bladder cancer. The sample providing as well as the providing of DNA from the samples is carried out according to standard procedures.
Wong I. H. N., et al. (2003) Clinical Cancer Research 9, 047-1052 describe a new method named RTQ-MSP which is a combination of MSP (methylation sensitive PCR) and real-time PCR. The authors demonstrate that a detection of a particular tumor-derived DNA sequence in plasma, serum and blood cells of already diagnosed hepatocellular carcinoma patients is possible.
U.S. Pat. No. 6,927,028 teaches a method for differentiating DNA species originating form cells of different individuals in biological samples by means of methylation specific PCR. The sample providing as well as the providing of DNA from the samples is carried out according to standard procedures.
Lecomte T., et al. (2002) Int. J. Cancer 100, 542-548 tested free-circulating DNA derived from plasma of colorectal cancer patients for the presence of KRAS2 mutations, for p16 gene promotor methylation, or both. The authors suggest, patients with free-circulating tumor-associated DNA in the blood have a lower probability of a 2-year recurrence-free survival than patients for who no free-circulating tumor-associated DNA in the blood is detected.